onedragon-anything/zenlesszonezero-onedragon

绝区零 一条龙 | 全自动 | 自动闪避 | 自动每日 | 自动空洞 | 支持手柄

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Summary Information

Updated 53 minutes ago
Added to GitGenius on September 9th, 2026
Created on June 7th, 2024
Open Issues & Pull Requests: 134 (+0)
GitHub issues: Enabled
Number of forks: 234
Total Stargazers: 7,117 (+0)
Total Subscribers: 13 (+0)

Repository Insights (GitGenius)

Median issue/PR response: 6.4 hours
Mean response time: 8.5 days
90th percentile: 16.3 days
Tracked items: 1,451

How this project is maintained

Around half of the issues opened in the past year never receive a reply. 68% of open issues come from outside the core team, a mix of external reports and the maintainers' own roadmap. Work labelled "Invalid | 无效反馈" is answered fastest, typically in under an hour, while "Stale | 杳无音信" waits about 3 days. Almost all tracked open issues have seen activity in the last three months. Only 9% of issues opened in the past year have been closed.

Charts & Analytics

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Issue Activity (beta)

Open issues: 79
New in 7 days: 8
Closed in 7 days: 3
Avg open age: 97 days
Stale 30+ days: 50
Stale 90+ days: 4

Recent activity

Opened in 7 days: 5
Closed in 7 days: 2
Comments in 7 days: 1
Events in 7 days: 4

Top labels

  • Bug | 工作不正常 (870)
  • Triage | 待检查 (661)
  • Enhancement | 增强 (268)
  • Invalid | 无效反馈 (119)
  • Need More Info | 需要更多信息 (54)
  • Cannot Reproduce | 无法复现 (50)
  • Adapting | 等待适配 (39)
  • Assigned | 正在处理 (33)

Detailed Description

ZenlessZoneZero-OneDragon is a game automation tool for Zenless Zone Zero that uses image recognition and automation to handle repetitive gameplay tasks.

The tool addresses the tedium of grinding and daily maintenance in the game by automating combat, dodging, and routine activities. It uses image and sound recognition models to identify game states and respond appropriately, combined with customizable logic for combat that supports skill markers, conditions, and variables. The dodge assistant integrates audio and visual analysis for high accuracy with low resource consumption. Daily cleanup automation covers shops, lotteries, cafes, materials, and rewards. The hollow combat module applies large-model-trained recognition and pathfinding capabilities.

The tool runs on Windows and is designed for players seeking to automate repetitive content without constant manual input. It suits anyone grinding materials or completing daily tasks in the game. The project explicitly disclaims any responsibility for account bans or other consequences, and warns against commercial resale or paid boosting services using this software.

The project maintains active engagement with its community through multiple official channels including documentation, a QQ community, and GitHub issues for feedback and discussion. Contributors are actively recruited with documented onboarding materials covering the technical stack and setup process. The codebase is written in Python and accepts community participation through established contribution guidelines.